README.md

metadata

annotations_creators:
  - crowdsourced
language_creators:
  - found
language:
  - en
license:
  - cc-by-4.0
multilinguality:
  - monolingual
size_categories:
  - 10K<n<100K
source_datasets:
  - original
task_categories:
  - multiple-choice
task_ids:
  - multiple-choice-qa
paperswithcode_id: cosmosqa
pretty_name: CosmosQA
dataset_info:
  features:
    - name: id
      dtype: string
    - name: context
      dtype: string
    - name: question
      dtype: string
    - name: answer0
      dtype: string
    - name: answer1
      dtype: string
    - name: answer2
      dtype: string
    - name: answer3
      dtype: string
    - name: label
      dtype: int32
  splits:
    - name: train
      num_bytes: 17156676
      num_examples: 25262
    - name: test
      num_bytes: 5120580
      num_examples: 6963
    - name: validation
      num_bytes: 2186585
      num_examples: 2985
  download_size: 12029581
  dataset_size: 24463841
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: test
        path: data/test-*
      - split: validation
        path: data/validation-*

Dataset Card for "cosmos_qa"

Table of Contents

• Dataset Description
  • Dataset Summary
  • Supported Tasks and Leaderboards
  • Languages
• Dataset Structure
  • Data Instances
  • Data Fields
  • Data Splits
• Dataset Creation
  • Curation Rationale
  • Source Data
  • Annotations
  • Personal and Sensitive Information
• Considerations for Using the Data
  • Social Impact of Dataset
  • Discussion of Biases
  • Other Known Limitations
• Additional Information
  • Dataset Curators
  • Licensing Information
  • Citation Information
  • Contributions

Dataset Description

• Homepage: https://wilburone.github.io/cosmos/
• Repository: https://github.com/wilburOne/cosmosqa/
• Paper: Cosmos QA: Machine Reading Comprehension with Contextual Commonsense Reasoning
• Point of Contact: Lifu Huang
• Size of downloaded dataset files: 24.40 MB
• Size of the generated dataset: 24.51 MB
• Total amount of disk used: 48.91 MB

Dataset Summary

Cosmos QA is a large-scale dataset of 35.6K problems that require commonsense-based reading comprehension, formulated as multiple-choice questions. It focuses on reading between the lines over a diverse collection of people's everyday narratives, asking questions concerning on the likely causes or effects of events that require reasoning beyond the exact text spans in the context

Supported Tasks and Leaderboards

More Information Needed

Languages

More Information Needed

Dataset Structure

Data Instances

default

• Size of downloaded dataset files: 24.40 MB
• Size of the generated dataset: 24.51 MB
• Total amount of disk used: 48.91 MB

An example of 'validation' looks as follows.

This example was too long and was cropped:

{
    "answer0": "If he gets married in the church he wo nt have to get a divorce .",
    "answer1": "He wants to get married to a different person .",
    "answer2": "He wants to know if he does nt like this girl can he divorce her ?",
    "answer3": "None of the above choices .",
    "context": "\"Do i need to go for a legal divorce ? I wanted to marry a woman but she is not in the same religion , so i am not concern of th...",
    "id": "3BFF0DJK8XA7YNK4QYIGCOG1A95STE##3180JW2OT5AF02OISBX66RFOCTG5J7##A2LTOS0AZ3B28A##Blog_56156##q1_a1##378G7J1SJNCDAAIN46FM2P7T6KZEW2",
    "label": 1,
    "question": "Why is this person asking about divorce ?"
}

Data Fields

The data fields are the same among all splits.

default

• id: a string feature.
• context: a string feature.
• question: a string feature.
• answer0: a string feature.
• answer1: a string feature.
• answer2: a string feature.
• answer3: a string feature.
• label: a int32 feature.

Data Splits

name	train	validation	test
default	25262	2985	6963

Dataset Creation

Curation Rationale

More Information Needed

Source Data

Initial Data Collection and Normalization

More Information Needed

Who are the source language producers?

More Information Needed

Annotations

Annotation process

More Information Needed

Who are the annotators?

More Information Needed

Personal and Sensitive Information

More Information Needed

Considerations for Using the Data

Social Impact of Dataset

More Information Needed

Discussion of Biases

More Information Needed

Other Known Limitations

More Information Needed

Additional Information

Dataset Curators

More Information Needed

Licensing Information

As reported via email by Yejin Choi, the dataset is licensed under CC BY 4.0 license.

Citation Information

@inproceedings{huang-etal-2019-cosmos,
    title = "Cosmos {QA}: Machine Reading Comprehension with Contextual Commonsense Reasoning",
    author = "Huang, Lifu  and
      Le Bras, Ronan  and
      Bhagavatula, Chandra  and
      Choi, Yejin",
    booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)",
    month = nov,
    year = "2019",
    address = "Hong Kong, China",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/D19-1243",
    doi = "10.18653/v1/D19-1243",
    pages = "2391--2401",
}

Contributions

Thanks to @patrickvonplaten, @lewtun, @albertvillanova, @thomwolf for adding this dataset.